code: def __init__(
      self, segment_length: int, context_length: int, rate_ratio: int
  ):
      self.segment_length = segment_length
      self.context_length = context_length
  
      self.context_length_v = context_length
      self.context_length_a = context_length * rate_ratio
      self.context_v = torch.zeros([self.context_length_v, 3, 340, 600])
      self.context_a = torch.zeros([self.context_length_a, 1])
  
imports: import numpy
  import sentencepiece
  import torch
  import torchaudio
  import torchvision
  import sys
  from avsr.data_prep.detectors.mediapipe.detector import LandmarksDetector
  from avsr.data_prep.detectors.mediapipe.video_process import VideoProcess
  from torchaudio.utils import download_asset
label_desc: Use image node_id 1 to create a new ContextCacher object  with example: obj = ContextCacher(segment_length, context_length, rate_ratio)